Neural Machine Translation: Google translate upping its game.

Google has announced that it will now be using Neural Machine Translation in its widely used language translation ecosystem. For those who don’t know what this is, it’s basically a change in the approach of translating sentences.

Previously, translation was done in fragments. The input sentence was broken up into small chunks and then the computer translated those small chunks, pieced them together and presented it to the user. While functional, the sentences that came out were largely cumbersome. They lacked the spontaneity of natural language, not to mention the grammatical precision. And this often led to a change of context with sentences missing large meanings due to a few ill placed words here and there. Neural Machine Translation is sort of like ‘taking a step back’ to see all of the sentence as opposed to just parts of it.

According to Wikipedia, “Neural machine translation (NMT) is the approach to machine translation in which a large neural network is trained to maximize translation performance. It is a radical departure from the phrase-based statistical translation approaches, in which a translation system consists of subcomponents that are separately optimized.”

Google says it was prompted to make the jump after exciting research results. They have also said that this will be “improving more in a single leap than we’ve seen in the last ten years combined.” This sort of development falls in line with google making its artificial intelligence (A.I) engine read romantic novelsin order to reproduce more natural responses.

At the moment, only 8 languages other than English support this significant upgrade. All to and from English. French, Turkish, Chinese, German, Spanish, Portuguese, Korean and Japanese. But Google certainly plans to integrate this technology into the 103 languages it now helps translate worldwide. Google translate has always been an exciting piece of software. And this step up is certainly a big milestone.

Learning a language can bear such importance. Be it for a cultural transition or an assignment or simply for the love of it. I think it’s fair to say, Google is doing a pretty good job by making this all the more easier.

Mahir Amer is a college student in Dhaka. He loves tech, designing, arts, sports and writing. Math and science too. He hopes to get admitted to an American University someday. Most of Mahir’s day is spent thinking about football or working on Adobe Illustrator. You can see his work at https://www.behance.net/mahiramer